Forecasting regional long-run energy demand: A functional coefficient panel approach

Abstract

Previous authors have pointed out that energy consumption changes both over time and nonlinearly with income level. Recent methodological advances using functional coefficients allow panel models to capture these features succinctly. In order to forecast a functional coefficient out-of-sample, we use functional principal components analysis (FPCA), reducing the problem of forecasting a surface to a much easier problem of forecasting a small number of smoothly varying time series. Using a panel of 180 countries with data since 1971, we forecast energy consumption to 2035 for Germany, Italy, the US, Brazil, China, and India. © 2021 Elsevier B.V.